Backend / DevOps Engineer – AI Infrastructure (Contract)

About the Company

A Series A AI infrastructure company based in California is building advanced training and evaluation systems for next-generation intelligent agents. Founded by researchers and engineers from leading AI and academic organizations, the company develops large-scale datasets, benchmarking systems, and reinforcement learning environments used by frontier AI labs and research teams.

The company operates at the intersection of applied AI research, distributed systems, and infrastructure engineering, with products already widely adopted across the AI ecosystem.

About the Role

The company is hiring Backend and DevOps Engineers to contribute to a new AI training initiative focused on creating realistic engineering scenarios for advanced AI systems.

This role is designed for engineers with genuine production experience operating backend systems and infrastructure at scale. You will transform real-world engineering incidents, outages, deployment challenges, scalability problems, and operational workflows into structured benchmark tasks used to train and evaluate AI agents.

This is a fully remote, contract-based role with flexible scheduling and output-based compensation.

Key Responsibilities

• Build and work across backend systems using Go, Python, Docker, gRPC, and Kubernetes-native tooling
• Document real-world infrastructure and DevOps scenarios based on hands-on engineering experience
• Create benchmark tasks involving CI/CD, observability, identity management, infrastructure-as-code, and distributed systems
• Contribute to secure and scalable Kubernetes-native architectures
• Collaborate with the internal research and engineering team to improve AI training workflows
• Deliver high-quality engineering outputs on a consistent cadence throughout the engagement

Required Qualifications

Technical Requirements

• 2–15 years of backend engineering experience with strong DevOps and infrastructure exposure
• Strong experience building and operating production backend services
• Deep expertise with Kubernetes, Terraform, and CI/CD systems
• Proficiency in Go, Python, or Java
• Experience with Docker, gRPC, and cloud-native services
• Hands-on experience with several of the following:Identity & Access Management (IAM)
  Observability tooling (Prometheus, Grafana)
  GitLab CI or similar CI/CD platforms
  Kubernetes ecosystem tools
  Infrastructure-as-Code practices
  

Execution & Communication

• Ability to work independently with minimal supervision
• Comfortable in flexible, output-driven environments
• Strong written English communication skills

Nice to Have

• Experience with secure or air-gapped deployments
• Distributed systems or ML infrastructure experience
• Exposure to AI benchmarking or AI training workflows
• Familiarity with GitLab CI

Ideal Candidate Profile

An experienced backend or infrastructure engineer who has operated real production systems at scale and enjoys translating hands-on engineering experience into structured technical documentation and workflows. Ideal candidates are autonomous, technically deep, and comfortable in fast-moving AI-focused environments.

Work Model & Compensation

• Fully remote, global
• Contract engagement (~3 months)
• Approximately 30–40 hours/week
• Flexible, output-based compensation model
• High earning potential based on approved deliverables and output quality

Hiring Process

• Technical assignment
• Final offer